Abstract
This paper addresses people re-identification problem for visual surveillance applications. Our approach is based on a rich description of each occurrence of a person thanks to a graph encoding of its salient points. People appearance in a video is encoded by bags of graphs whose similarities are encoded by a graph kernel. Such similarities combined with a tracking system allow us to distinguish a new person from a re-entering one into a video. The efficiency of our method is demonstrated through experiments.
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Mahboubi, A., Brun, L., Conte, D., Foggia, P., Vento, M. (2013). Tracking System with Re-identification Using a Graph Kernels Approach. In: Wilson, R., Hancock, E., Bors, A., Smith, W. (eds) Computer Analysis of Images and Patterns. CAIP 2013. Lecture Notes in Computer Science, vol 8047. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40261-6_48
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DOI: https://doi.org/10.1007/978-3-642-40261-6_48
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